CAMSHIFT Tracker Design Experiments With Intel OpenCV and SAI
UNIVERSITY OF SOUTHERN CALIFORNIA LOS ANGELES INST FOR ROBOTICS AND INTELLIGENT SYSTEMS
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When humans interact with computer systems, they expect the experience to meet human standards of reactiveness, robustness and, if possible, non-intrusiveness. In order for computer vision techniques to have a significant impact in human-computer interaction, the development of efficient and robust algorithms, as well as their integration and operation as part of complex including multi-modal systems, must be specifically addressed. This report describes design and implementation experiments for CAMSHIFT-based tracking systems using Intels Open Computer Vision library and SAI Software Architecture for Immersipresence, a software architecture model created specifically to address the integration of different solutions to technical challenges, developed independently in separate fields, into working systems, that operate under hard performance constraints. Results show that the SAI formalism is an enabling tool for designing, describing and implementing robust systems of efficient algorithms.
- Human Factors Engineering and Man Machine Systems